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Source Transformation

Source Transformation

Source transformation is a fundamental technique employed in circuit analysis, offering a valuable tool for simplifying complex electrical circuits. This technique involves the replacement of either a voltage source in series with a resistor by a current source in parallel with a resistor, or vice versa. The key concept here is that when the original sources are deactivated (turned off), the equivalent resistance at the circuit's end terminals remains the same.
It is essential to note that when...

Transformation

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Microbial communities are dynamic environments where cell lysis releases free DNA into the surroundings. Other cells can take up this extracellular DNA through a process known as transformation.When a cell incorporates this foreign DNA into its genome, resulting in genetic modification, the process is known as transformation. Cells capable of this process are termed competent. Competence can be natural, as observed in certain bacteria and archaea, or artificially induced in the...

Transformation of Plane Strain

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Source Transformation for AC Circuits

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Deconvolution

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Related Experiment Video

Updated: Jul 14, 2026

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

Multisource image fusion method using support value transform.

Sheng Zheng¹, Wen-Zhong Shi, Jian Liu

¹Institute of Intelligent Vision and Image Information Best, College of Electrical and Information Engineering, China Three Gorges University, Yichang 443002, China. zsh@ctgu.edu.cn

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|July 4, 2007

Summary

This study introduces a novel image fusion method using support value transform for enhanced feature representation. The approach, utilizing mapped least squares SVM, outperforms traditional methods in multisource image fusion tasks.

Related Experiment Videos

Last Updated: Jul 14, 2026

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

Area of Science:

Computer Vision
Image Processing
Machine Learning

Background:

Multiple imaging sensors capture diverse data, but no single sensor provides a complete picture.
Image fusion combines information from multiple sensors into a single, comprehensive image.
Existing fusion methods like Laplacian pyramid and discrete wavelet transform have limitations.

Purpose of the Study:

To propose a new image fusion method based on support value transform.
To leverage support values from Support Vector Machines (SVMs) for salient feature representation.
To enhance image fusion by utilizing an undecimated transform-based approach.

Main Methods:

Developed a novel image fusion method using support value transform.
Employed mapped least squares Support Vector Machines (LS-SVM) to compute image support values.
Utilized multiscale support value filters derived from LS-SVM for feature extraction.
Implemented an undecimated transform-based approach for image fusion.

Main Results:

The proposed method effectively represents salient image features using support values.
Fusion experiments on multisource images demonstrated superior performance compared to conventional methods.
Quantitative evaluation using metrics like Quality of Visual Information (Q(AB/F)) and mutual information confirmed effectiveness.

Conclusions:

The support value transform offers a powerful new approach for image fusion.
The proposed method provides superior fusion results for multisource images.
This technique enhances the preservation of relevant information in fused images.